Electronic devices and methods for recognizing driving behavior are provided. The electronic devices may perform the methods to obtain first electronic signals encoding movement data associated with the electronic device from the at least one sensor at a target time point; operate logic circuits to determine whether the first electronic signals encoding movement data meets a precondition; and upon the first electronic signals encoding movement data meeting the precondition, send second electronic signals encoding movement data within a predetermined time period associated with the target time point to a remote server.

Various implementations include approaches for training a surface detection classifier and detecting characteristics of a surface, along with related micromobility vehicles. Certain implementations include a method including: comparing: i) detected movement of a micromobility (MM) vehicle or a device located with a user at the MM vehicle while operating the MM vehicle, with ii) a surface detection classifier for the MM vehicle; and in response to detecting that the MM vehicle is traveling on a restricted surface type for a threshold period, performing at least one of: a) notifying an operator of the MM vehicle about the travel on the restricted surface type, b) outputting a warning at an interface connected with the MM vehicle or the device, c) limiting a speed of the MM vehicle, or d) disabling operation of the MM vehicle.

Various implementations include approaches for training a surface detection classifier and detecting characteristics of a surface, along with related micromobility vehicles. Certain implementations include a method including: comparing: i) detected movement of a micromobility (MM) vehicle or a device located with a user at the MM vehicle while operating the MM vehicle, with ii) a surface detection classifier for the MM vehicle; and in response to detecting that the MM vehicle is traveling on a restricted surface type for a threshold period, performing at least one of: a) notifying an operator of the MM vehicle about the travel on the restricted surface type, b) outputting a warning at an interface connected with the MM vehicle or the device, c) limiting a speed of the MM vehicle, or d) disabling operation of the MM vehicle.

System, methods, and other embodiments described herein relate to improving monitoring of traffic flows. In one embodiment, a method includes aggregating perception data associated with a road network from information sources to a server over a network. The method also includes generating a graph structure from the perception data in association with a neural network model. The graph structure is an incomplete representation of the road network in view of missing data. The method also includes completing the graph structure using the neural network model that forms a graph model of the traffic flows to de-noise the graph structure according to road constraints between two points in the road network. The method also includes communicating the graph model of the traffic flows to a vehicle to navigate traffic in the road network.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for monitoring a dedicated roadway the runs in parallel to a railroad. In some implementations, a system includes a central server, an interface, and sensors. The interface receives data from a railroad system that manages the railroad parallel to the dedicated roadway. The sensors are positioned in a fixed location relative to the dedicated roadway. Each sensor can detect vehicles in a first field of view on the dedicated roadway. For each detected vehicle, each sensor can generate sensor data based on the detected vehicle in the dedicated roadway and the data received at the interface. Each sensor can generate observational data and instruct the detected vehicle to switch to an enhanced processing mode. Each sensor can determine an action for the detected vehicle to take based on the generated observational data.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for monitoring a dedicated roadway the runs in parallel to a railroad. In some implementations, a system includes a central server, an interface, and sensors. The interface receives data from a railroad system that manages the railroad parallel to the dedicated roadway. The sensors are positioned in a fixed location relative to the dedicated roadway. Each sensor can detect vehicles in a first field of view on the dedicated roadway. For each detected vehicle, each sensor can generate sensor data based on the detected vehicle in the dedicated roadway and the data received at the interface. Each sensor can generate observational data and instruct the detected vehicle to switch to an enhanced processing mode. Each sensor can determine an action for the detected vehicle to take based on the generated observational data.

An alert system and method comprising at least one alert beacon having one or more sensors (e.g., LiDAR sensor). The alert beacon further including a processor operable to poll the LiDAR sensor for a predefined number of beta readings in response to receiving an initial reading from the LiDAR sensor indicating a vehicle is within a predefined distance away from the alert beacon. The processor further being operable to calculate an average distance and an average velocity for the vehicle in response to receiving the predefined number of beta readings when the vehicle is within the predefined distance from the alert beacon. The processor also being operable to activate an audible alert and a visual alert when the average distance is below a distance threshold and the average velocity exceeds a velocity threshold in response to calculating the average distance and the average velocity.

The present method permits to get real-time traffic data by the mean of pictures took by a series of georeferenced and synchronized high speed cameras installed on the portions of the road. These pictures and these data will be transferable by a secure means such as 5G or any other fast and secure technology on a server and accessible by cloud computing. Picture processing is carried out by photogrammetric, triangulation and picture recognition approaches in order to extract the position of each vehicle, pedestrian, cyclist or any object and identify its x, y, z coordinates in a local or global referencing system. This method permits to count the flow of traffic (vehicles, pedestrians, etc.) passing through these roads portions, to reproduce the real movements of vehicles, pedestrians and any object moving on a road, make simulations with a computer and intervene remotely in real-time to manage traffic.

Disclosed are methods and systems for improving the safety of an intersection. One or more sensor readings can be received. The one or more sensor readings can be compared to one or more thresholds. A signal can be provided to one or more lighting devices based on whether the one or more sensor readings satisfy the one or more thresholds.

Disclosed are methods and systems for improving the safety of an intersection. One or more sensor readings can be received. The one or more sensor readings can be compared to one or more thresholds. A signal can be provided to one or more lighting devices based on whether the one or more sensor readings satisfy the one or more thresholds.